Image Based Identification of Ghanaian Timbers Using the XyloTron: Opportunities, Risks and Challenges
Item
Title
Image Based Identification of Ghanaian Timbers Using the XyloTron: Opportunities, Risks and Challenges
Date
2019
Language
english
Abstract
Computer vision systems for wood identification have the potential to empower
both producer and consumer countries to combat illegal logging if they can be
deployed effectively in the field. In this work, carried out as part of an active
international partnership with the support of UNIDO, we constructed and curated
a field-relevant image data set to train a classifier for wood identification of 15
commercial Ghanaian woods using the XyloTron system. We tested model performance
in the laboratory, and then collected real-world field performance data across
multiple sites using multiple XyloTron devices. We present efficacies of the trained
model in the laboratory and in the field, discuss practical implications and challenges
of deploying machine learning wood identification models, and conclude
that field testing is a necessary step - and should be considered the gold-standard -
for validating computer vision wood identification systems
both producer and consumer countries to combat illegal logging if they can be
deployed effectively in the field. In this work, carried out as part of an active
international partnership with the support of UNIDO, we constructed and curated
a field-relevant image data set to train a classifier for wood identification of 15
commercial Ghanaian woods using the XyloTron system. We tested model performance
in the laboratory, and then collected real-world field performance data across
multiple sites using multiple XyloTron devices. We present efficacies of the trained
model in the laboratory and in the field, discuss practical implications and challenges
of deploying machine learning wood identification models, and conclude
that field testing is a necessary step - and should be considered the gold-standard -
for validating computer vision wood identification systems
Collection
Citation
“Image Based Identification of Ghanaian Timbers Using the XyloTron: Opportunities, Risks and Challenges,” CSIRSpace, accessed December 22, 2024, http://cspace.csirgh.com/items/show/1833.